#3.2 Distribution of coat length given the country (cold/hot)
#cold = ND, MN, ME
#hot = FL, LA, AZ
states = pd.Series(0, index=['ND', 'MN', 'ME', 'FL', 'LA', 'AZ'])
top_labels = ['Short', 'Medium', 'Long']
colorsCold = ['rgba(38, 24, 74, 0.8)', 'rgba(71, 58, 131, 0.8)', 'rgba(122, 120, 168, 0.8)']
colorsHot = ['rgba(165, 42, 42, 0.8)', 'rgba(204, 85, 0, 0.8)', 'rgba(233, 116, 81, 0.8)']
mask = df['contact_state'].isin(states.index)
x_data_s = df.loc[(df['coat'] == 'Short') & mask].groupby('contact_state')['contact_state'].count()
x_data_m = df.loc[(df['coat'] == 'Medium') & mask].groupby('contact_state')['contact_state'].count()
x_data_l = df.loc[(df['coat'] == 'Long') & mask].groupby('contact_state')['contact_state'].count()
x_data_s = x_data_s.reindex(states.index, fill_value=0)
x_data_m = x_data_m.reindex(states.index, fill_value=0)
x_data_l = x_data_l.reindex(states.index, fill_value=0)
x_data = []
for x in range(len(states)):
row = []
tot = x_data_s[x] + x_data_m[x] + x_data_l[x]
row.append(x_data_s[x] / tot * 100)
row.append(x_data_m[x] / tot * 100)
row.append(x_data_l[x] / tot * 100)
x_data.append(row)
y_data = ['North Dakota', 'Minnesota', 'Maine', 'Florida', 'Lousiana', 'Arizona']
fig = go.Figure()
for i in range(0, len(x_data[0])):
count = 0;
for xd, yd in zip(x_data, y_data):
# differentiate color for hot and cold states
if(count > 2):
fig.add_trace(go.Bar(
x=[xd[i]], y=[yd],
orientation='h',
marker=dict(
color=colorsHot[i],
line=dict(color='rgb(248, 248, 249)', width=1)
)
))
else:
fig.add_trace(go.Bar(
x=[xd[i]], y=[yd],
orientation='h',
marker=dict(
color=colorsCold[i],
line=dict(color='rgb(248, 248, 249)', width=1)
)
))
count = count + 1
fig.update_layout(
xaxis=dict(
showgrid=False,
showline=False,
showticklabels=False,
zeroline=False,
domain=[0.15, 1]
),
yaxis=dict(
showgrid=False,
showline=False,
showticklabels=False,
zeroline=False,
),
barmode='stack',
paper_bgcolor='rgb(248, 248, 255)',
plot_bgcolor='rgb(248, 248, 255)',
margin=dict(l=120, r=10, t=140, b=80),
showlegend=False,
)
annotations = []
for yd, xd in zip(y_data, x_data):
# labeling the y-axis
annotations.append(dict(xref='paper', yref='y',
x=0.14, y=yd,
xanchor='right',
text=str(yd),
font=dict(family='Arial', size=14,
color='rgb(67, 67, 67)'),
showarrow=False, align='right'))
# labeling the first Likert scale (on the top)
if yd == y_data[-1]:
annotations.append(dict(xref='x', yref='paper',
x=xd[0] / 2, y=1.1,
text=top_labels[0],
font=dict(family='Arial', size=14,
color='rgb(67, 67, 67)'),
showarrow=False))
space = xd[0]
for i in range(1, len(xd)):
# labeling the Likert scale
if yd == y_data[-1]:
annotations.append(dict(xref='x', yref='paper',
x=space + (xd[i]/2), y=1.1,
text=top_labels[i],
font=dict(family='Arial', size=14,
color='rgb(67, 67, 67)'),
showarrow=False))
space += xd[i]
fig.update_layout(title='Coat length given the state', annotations=annotations)
fig.update_layout(height = 600)
fig.update_traces(textposition='inside', texttemplate = "%{x:.1f}%", textangle=0)
fig.show()
